Table 2.
Area under ROC curves from different methods for Exon array data
|
Methods |
2 replicates |
5 replicates |
||||||
|---|---|---|---|---|---|---|---|---|
| 1 | 2 | 3 | 4 | 5 | Average | |||
|
t-test |
RMA |
0.8945 |
0.8909 |
0.9107 |
0.9346 |
0.9316 |
0.9118 |
0.9475 |
| |
PLIER |
0.8806 |
0.8852 |
0.9004 |
0.9084 |
0.9083 |
0.8937 |
0.9291 |
| |
GME |
0.9082 |
0.9044 |
0.9415 |
0.9544 |
0.9427 |
0.9287 |
0.9580 |
| PPLR_1000 |
RMA |
0.9243 |
0.9234 |
0.9385 |
0.9417 |
0.9387 |
0.9323 |
0.9489 |
| |
GME |
0.9208 |
0.9093 |
0.9365 |
0.9297 |
0.8969 |
0.9188 |
0.9447 |
| *PPLR_10000 |
RMA |
0.9227 |
0.9226 |
0.9419 |
0.9453 |
0.9432 |
0.9348 |
0.9492 |
| |
GME |
0.9353 |
0.9317 |
0.9474 |
0.9374 |
0.9324 |
0.9274 |
0.9503 |
| IPPLR |
RMA |
0.9246 |
0.9301 |
0.9464 |
0.9468 |
0.9463 |
0.9382 |
0.9493 |
| GME | 0.9379 | 0.9391 | 0.9457 | 0.9597 | 0.9549 | 0.9475 | 0.9589 | |
Gene expression estimation methods are combined with different finding-DE-gene methods. PPLR and IPPLR require a level of uncertainty associated with expression estimation, and they are therefore combined with GME and RMA since these two methods can provide variance of gene expression measurements. For t-test we use only the point estimates of gene expression. PLIER provides only a point estimate for gene expression and we only evaluate it combining with t-test. The number after PPLR indicates the sample number used in the importance sampling of the algorithm. The best result for each comparison is highlighted in bold.